Machine Learning Principal Solutions Architect

Jobgether • United States

Remote

This Job is No Longer Active This position is no longer accepting applications

AI Summary

Lead strategic AI and machine learning initiatives for enterprise clients, shaping intelligent data solutions from vision to production. Own end-to-end ML architecture, deployment, monitoring, and lifecycle management across complex client engagements. Requires 10+ years of production-scale ML experience, strong technical leadership, and consulting expertise.

Key Highlights

Lead end-to-end ML architecture and lifecycle management for enterprise clients

Design scalable AI solutions with data scientists, engineers, and platform teams

Remote-first role with autonomy, technical excellence, and continuous learning

Key Responsibilities

Lead the end-to-end architecture, implementation, and lifecycle management of AI and machine learning solutions for strategic client engagements

Own solution design and delivery across the full ML lifecycle, including model development environments, deployment strategies, monitoring, retraining, and production operations

Translate complex business objectives and data science requirements into secure, scalable, and resilient technical architectures

Design and optimize environments that enable data scientists and engineers to build, train, test, and deploy machine learning models using client data

Build and maintain robust data pipelines by integrating information from multiple sources and preparing data environments for analytics and ML applications

Define production infrastructure, deployment approaches, and operational strategies to ensure reliable consumption and maintenance of AI solutions

Partner with data scientists to transform data into actionable insights and production-ready machine learning models

Develop testing, quality assurance, validation, and monitoring strategies to ensure solution reliability, performance, and observability

Collaborate with Sales and account leadership to support client growth, identify new opportunities, and strengthen long-term partnerships

Serve as a trusted technical advisor to senior and executive stakeholders, guiding AI/ML roadmaps and strategic decisions

Lead architecture discussions, discovery workshops, technical reviews, and complex problem-solving sessions with clients

Act as a technical escalation point for challenging AI/ML initiatives and ensure successful project outcomes

Contribute to internal AI/ML capabilities through reusable frameworks, accelerators, reference architectures, documentation, and best practices

Mentor engineers, data scientists, and technical team members to strengthen consulting and delivery expertise

Help establish scalable delivery standards while promoting customer success, innovation, and technical excellence

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Technical Skills Required

Python Machine Learning Cloud Architecture

Benefits & Perks

Remote-first work environment

Competitive compensation package

401(k) plan with company matching

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Nice to Have

Preferred experience with cloud and AI ecosystems such as AWS, Azure, GCP, Snowflake, Databricks, or similar platforms

Preferred experience with ML frameworks and tools including TensorFlow, Keras, scikit-learn, H2O, MLflow, AWS SageMaker, or Azure ML

Familiarity with containerization and orchestration technologies such as Docker and Kubernetes is a plus

Experience in consulting environments or contributing to technical communities, open-source projects, publications, or industry events is beneficial

Job Description

This role offers the opportunity to lead complex AI and machine learning initiatives for enterprise clients while shaping the future of intelligent data solutions.You will take ownership of strategic ML architecture, from initial vision and design through deployment, optimization, and long-term operations.The position combines deep technical expertise, consulting leadership, and customer partnership to deliver measurable business outcomes.You will collaborate with data scientists, engineers, platform teams, and executive stakeholders to build scalable AI solutions.

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